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From |
Ridhima Gupta <g.ridhima@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
st: testing fixed effects versus random effects for clustered data using overiden |

Date |
Mon, 28 Feb 2011 14:46:15 +0000 |

Hello, I don't have a panel data in the strict sense of the term i.e. I have data on farmers who have several plots/fields. I first perform a standard hausman test and I do not reject the null hypothesis of random effects. The result is as follows: hausman fixed ., sigmamore ---- Coefficients ---- | (b) (B) (b-B) sqrt(diag(V_b-V_B)) | fixed . Difference S.E. -------------+---------------------------------------------------------------- Happy_Seeder | .1271123 .5428827 -.4157704 .429518 Rotavator | -.3621306 -.3157851 -.0463455 .840699 Seed_Drill | -.083707 .860967 -.944674 .5539517 quantity_s~c | .0056369 -.0031733 .0088101 .0188915 plotsize_hec | .0252054 .0310519 -.0058465 .0525993 ferti_hec | .0027516 .003003 -.0002514 .0045816 exp_weedi_~s | .1077859 .0282141 .0795719 .0585852 soil_type_1 | -1.034988 -1.900228 .8652395 .6801256 soil_type_2 | -.4202215 -2.165068 1.744846 .8051986 ------------------------------------------------------------------------------ b = consistent under Ho and Ha; obtained from xtreg B = inconsistent under Ha, efficient under Ho; obtained from xtreg Test: Ho: difference in coefficients not systematic chi2(9) = (b-B)'[(V_b-V_B)^(-1)](b-B) = 12.70 Prob>chi2 = 0.1766 But when I perform the robust version of this test, I reject the null hypothesis of random effects. Random-effects GLS regression Number of obs = 227 Group variable: hh_id Number of groups = 86 R-sq: within = 0.0106 Obs per group: min = 1 between = 0.0922 avg = 2.6 overall = 0.0674 max = 6 Random effects u_i ~ Gaussian Wald chi2(9) = 15.76 corr(u_i, X) = 0 (assumed) Prob > chi2 = 0.0720 (Std. Err. adjusted for 86 clusters in hh_id) ------------------------------------------------------------------------------ | Robust yield_per_~c | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- Happy_Seeder | .5428827 1.024596 0.53 0.596 -1.465289 2.551054 Rotavator | -.3157851 1.425605 -0.22 0.825 -3.10992 2.47835 Seed_Drill | .860967 1.036252 0.83 0.406 -1.170049 2.891983 quantity_s~c | -.0031733 .041733 -0.08 0.939 -.0849685 .078622 plotsize_hec | .0310519 .0467653 0.66 0.507 -.0606065 .1227103 ferti_hec | .003003 .0053299 0.56 0.573 -.0074435 .0134495 exp_weedi_~s | .0282141 .0792311 0.36 0.722 -.1270759 .1835041 soil_type_1 | -1.900228 .7639786 -2.49 0.013 -3.397599 -.4028574 soil_type_2 | -2.165068 .8668351 -2.50 0.013 -3.864033 -.4661022 _cons | 41.85728 4.370738 9.58 0.000 33.29079 50.42376 -------------+---------------------------------------------------------------- sigma_u | 4.4041886 sigma_e | 4.0351113 rho | .54364968 (fraction of variance due to u_i) ------------------------------------------------------------------------------ . xtoverid Test of overidentifying restrictions: fixed vs random effects Cross-section time-series model: xtreg re robust cluster(hh_id) Sargan-Hansen statistic 26.327 Chi-sq(9) P-value = 0.0018 Is there any inconsistency here? Are there any tests in the literature that allow me to test the assumption of homoskedasticity and no auto-correlation in the random effects model? Thanks a lot, Ridhima * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

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